Effective memory is crucial for LLM agents, yet constructing it effectively remains challenging. A memory-construction policy decides what information to extract, store, update, compress, or discard as interactions accumulate. Heuristic memory methods rely on subjective, task-specific rules, which can misalign with dow...
Experiments show that AttriMem outperforms retrieval-based, heuristic, and RL-based baselines, generalizes across benchmarks and answer models, stabilizes RL optimization, and outperforms retrieval-based, heuristic, and RL-based baselines on long-horizon dialogue question answering.
Qin-Feng Li, Yun-Tai Bao, Xinyang Yu et al.· 0 citations
SkillAligner is proposed, a training-free execution-time skill adaptation framework that treats retrieved skills as adaptable drafts rather than fixed instructions that substantially improves task performance over existing skill-use baselines, reduces skill-induced regressions at the instance level, and lowers total in...
Qin-Feng Li, Dalin He, Yun-Tai Bao et al.· 0 citations
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